Tag Archives: CHANGED

In the previous part of this blog we saw how network operators need fresh approaches in order to generate new revenue and hold up their profitability in a challenging and fast-evolving market. In this part, Joerg Koenig, TIBCO’s director of Vertical Solutions, explains two more reasons for changed market.

The issues that lie behind the model

So far, so good. But what are the challenges of this new model? How does it work in practical terms? On the path to digital transformation, where are the stumbling blocks?

To begin with, the telco must realize that this change in business model will lead to billing flexibility, away from minutes, bytes and message volumes and towards value-based pricing. In other words, the telco can base pricing on the value of a transaction or the service being consumed, as opposed to the number of bytes consumed. This does create challenges for the telco around the valuation of a transaction or service, and thus makes it useful for the telco to have the right tools so that they can manage and monitor what is really going on with traffic.

Transforming a telco business to take advantage of this new operating model will be all about integration and automation. The telco operates a broad web of applications from its core to edge and will need to support much higher levels of unpredictable scaling that will be inevitable with an on-demand model. Some of these applications will have to be migrated, replaced by SaaS applications, or deployed into different private or public clouds and platforms.

Some will have to be kept on premise for data legality or latency reasons, or perhaps re-written to support a microservice architecture. Furthermore, the rise of IoT will mean integration of new devices that will require data aggregation and filtering. This wide range of architecture, deployment, scaling, and performance choices will change over time and will require a matching integration capability that will support future innovation.

Essential to the telco cloud model will be the success with which APIs are made available by the telco to third parties. Providing easily consumable, well packaged API products, will attract partners and so drive revenues and business growth. In a platform model, APIs will be the ‘face’ of the telco and the ease with which they can be deployed, tried and consumed will provide crucial differentiation. The speed with which they can be created, tailored, managed and secured to protect backend systems will be critical.

Unpredictability is the new normal. Once APIs are published, the take up from customers and partners should lead both to great success and also to unforeseen levels of usage. There will inevitably be a feeling that the telco is losing control of the API. This is a very different model from the classical subscriber growth approach, and will need a very different mindset.

All of this on-demand network configuration from customers and partners, added to the effect of billions of connected IoT devices, brings the need to monitor and manage decisions in real time in a way that is bigger than any sort of human interaction can cope with. This means that all aspects of OSS/BSS orchestration, configuration and operation will trend towards automation. This necessitates deep and wide advanced analytics and the use of lightweight, real-time algorithms to detect and trigger action, deployed from core systems right out to devices on the edge of the network.

Finally, as the telco network becomes more programmable and network functions become virtualized, the promise of a reduced cost of ownership will be realised. Added to this are the value benefits of the platform approach once an ecosystem of partners can, via a self-service portal and APIs, configure new services on demand. Maximizing the value that the telco can derive from this, requires that the entire OSS/BSS stack be in alignment.

Everything from on-boarding customers and partners, executing on demand order and service orchestration to network configuration, tailored pricing, end to end assurance and all across physical, virtual and third-party networks and services will need to support the telco cloud platform. The wide variety of possible users and services means that such processes must be automatically generated, not simply scripted or coded.

Time to lead, not follow

We have seen that it is no longer sustainable to base a telco business around old ways of delivering and charging for services. The old-school linear pipeline where customers buy the capacity they need from operators via a conventional supply chain is on the way out. It no longer meets requirements. This creates an opportunity for telcos to reinvent the basis on which capacity is supplied. The successful telco will be a leader and innovator in this dynamic ecosystem, not a follower. They will need to show this leadership in numerous ways, for example by embracing a software-driven automated approach to network provisioning and management, and by enabling partners to work with them on taking their business in new directions. There is a need for a bold and decisive approach, and the time for that is now.

Network operators need fresh approaches in order to generate new revenue and hold up their profitability in a challenging and fast-evolving market. By basing their business around a cloud-based platform model, they can ensure their survival in a world of unpredictable traffic patterns and massive data growth. Joerg Koenig, director Vertical Solutions, here at TIBCO, examines the dividends, challenges, and practicalities of such a move.

Time to take back control

The historic way in which telco business has been conducted must change. The model of locking the customer into your network and billing them for it in ways that do not necessarily match their consumption is redundant.

Today’s consumers see connectivity as just another commodity, a utility they depend on, but which they largely take for granted. What excites people is not the connection itself, but the data and content that travels over it. This is why telco Over-The-Top (OTT) service providers have been able to achieve so much success—success which has largely come at the expense of the network operator. Not only have OTTs eroded telco revenues, they have damaged the perceived relevance and centrality of the telco by relegating them to a mere pipe for their services, an undistinguished highway between locations.

There are other issues with traditional telco business practices. Network availability has traditionally been dimensioned to support maximum peaks of traffic. This guarantees that a network will be both expensive to build and massively underemployed for most of the time.

The arrival of the software-driven, virtualized network has helped to address the problem of network build costs. Now it’s time for operators to complete the job of grabbing back control by cutting the cost of driving revenue. They can do this by adopting the model of the Telco Cloud—telecoms delivered as a service over a cloud-based platform.

The Telco cloud

The old ‘consumption model’—where telco customers are charged on the basis of a predetermined level of usage—does not fit well with current needs. Consumption patterns, driven by the effect of social media and other forms of rich content, are far less predictable than they were when this model was conceived.

There is an opportunity for bold and far-sighted telcos to reinvent the basis on which capacity is supplied. They must position themselves so that customers see them as suppliers of ‘telco as a service’ instead. This platform-based model is perfectly in tune with what their customers, both on the consumer and enterprise side, really want. A platform-based model enables on-demand scaling and agile, rapid delivery of new services, and is geared to meet the most unpredictable of peaks and troughs.

The model works best when it leaves the creation of these services in the hands of an ecosystem of newly empowered customers and partners, reliant on the telco’s core strength of providing ubiquitous mobile and wireless data connectivity. This has positive implications for revenue, as effectively the telco is providing an army of vertical market specialists with an advanced platform for their products, and letting them do the selling. This means, the old one-size-fits-all linear value chain is broken down into what is effectively a network of smaller value chains. No longer confined to only being able to grow their business by growing the number of subscribers—and without having to resort to price cutting as their best means of competing with rivals—the telco is free to participate in an infinite number of revenue-spinning vertical use cases and new initiatives.

Mainframes have one of the longest histories of any kind of computing technology that is still used today. In fact, mainframe history is far too long to pack into a single blog post. But I’m going to try anyway. Keep reading for a (very) brief history of mainframe computing.

Before diving in, let’s take a moment to appreciate just how long mainframes have been around.

Very few of the computer scientists who worked on the first mainframes are still working with mainframes today. That makes mainframes different than virtually all other computing technologies that we use today.

For example, plenty of people who work as Windows and Linux server admins today can remember when Windows came out in the 1980s, or when System V was the hottest new technology in the Unix world. Most people who support cell phones remember when the first cell phones appeared. Data scientists who work with Hadoop or Spark can certainly remember when those platforms came out; they’re still quite new compared to mainframes.

But few of the people who work with mainframes today can recall when the first mainframes came out.

Milestones in Mainframe History

That’s why it’s worth surveying major milestones in the development of mainframes over the years. They give you valuable perspective on just how significantly mainframes have evolved to become the lean, mean computing workhorses that they are today.

Major developments in mainframe history include:

First mainframe

By most measures, the first mainframe computer was the Harvard Mark I. Developed starting in the 1930s, the machine was not ready for use until 1943. It weighed five tons, filled an entire room and cost about $ 200,000 to build – which is something like twenty-eight million in 2017 money. (Keep that in mind the next time you complain about the cost of your iPhone.)

ENIAC

World War II sparked the creation of the next famous mainframe computer, the ENIAC (Electronic Numerical Integrator and Computer). Although the ENIAC was not actually completed until a year after the war ended, it signaled the start of heavy government investment in mainframe development. The ENIAC remained in service for a decade.

Magnetic storage

While early mainframes were based on vacuum tubes for storing data, a major innovation came to the mainframe world with the development of what was called core memory. In place of vacuum tubes, core memory stores information magnetically. Your magnetic 5400-RPM hard disk it was not, but core memory provided a faster and more reliable way to store and retrieve data than vacuum tubes. Core memory was first used in 1953 and soon replaced vacuum tubes entirely.

COBOL

COBOL, the programming language most closely associated with mainframes, debuted all the way back in 1959 and remains in widespread use today. That makes COBOL one of the oldest continuously used programming languages. It beats even C, which originated in the early 1970s.

Mainframe vendors

It’s worth noting that some of the companies involved in early mainframe development. IBM is the name most closely associated with mainframes. But historically, the mainframe commercial ecosystem was more diverse. More than half-dozen companies – including Univac, General Electric, and RCA – also sold mainframes during the first few decades of mainframe computing.

Linux for mainframes

Also worth noting is that, while mainframes for the first decades of their history ran on special mainframe operating systems, by the late 1990s this changed. Starting in 1998, IBM began developing a Linux-based operating system that could run on mainframes in place of mainframe-native systems.

Mainframes Today

Today, mainframes are much smaller and more agile than they were decades ago.

IBM mainframes are now about the size of a refrigerator. Modern mainframes don’t weigh more than a (very heavily packed) car.

They cost a lot less, too. Although IBM mainframes still had price tags in the million-dollar range in the early 2000s, today you can pick one up for closer to $ 100,000.

Conclusion

Over the past half-century of mainframe history, the machines have evolved rapidly and remarkably. Modern mainframes are hardly the huge, crazily expensive, unwieldy machines of yore. They readily integrate legacy with modern technologies, allowing you to do things like run COBOL apps on z/OS alongside Docker containers on Linux (using z/VM) on the same physical machine.

In 2006, HubSpot, a marketing services and software company, articulated the notion of inbound marketing.

Unlike traditional outbound marketing, companies use content in inbound marketing as a tool to drive prospects to websites to learn more about products and services. In 2006, inbound marketing was new to marketers’ toolboxes, but it swiftly became an appealing alternative to outbound email blasts and buying ad space in the vain hope for a boost in leads. Inbound marketing is designed to target the right buyers with the right messages at the right time in their buying process, so it’s considered more nuanced than traditional outbound methods. With more discriminating consumers, inbound marketing tries to engage customers more than simply sell to them. That’s a tall order, when according to “The State of Inbound 2016,” 40% of sales reps say that getting a response from prospects has gotten more difficult.

At root, inbound marketing is an approach that recognizes that the customer lifecycle has changed, and traditional sales has less of a role in that lifecycle. Consumers do more research online (as much as 80% of the former sales process may take place online), and sales representatives aren’t involved until later stages of the buying process. In addition, in the age of the customer, savvy consumers have more power in sales transactions. Inbound marketing seeks to exploit this new dynamic by helping consumers gather education and research as they go through the buying process.

During his keynote at the recent Inbound 2016 conference, Brian Halligan, CEO and co-founder of HubSpot, held forth on some of the sales and marketing trends that took shape in 2006 with the introduction of inbound marketing and how trends like inbound have changed the sales cycle so dramatically today.

How a new sales cycle has changed marketing

Buyer choice has expanded. In 2006, Halligan said, prospects had between four and five vendors to choose from for any given product. Now, they have between 14 and 15 different vendors for any given product or service. This overwhelming choice is a function of supply and demand mismatches.

If you’re not marketing inside the [Mark] Zuckerberg universe, you might as well be marketing inside a trashcan. Brian HalliganCEO and co-founder, HubSpot

“Supply is up — way up,” Halligan said. “It has become so much easier to … build useful stuff. Things like agile methodologies and open APIs have made it much easier to build products. Supply is up, but at the same time, demand is flat.”

Halligan also noted that vendors have additional pressure to stand out from the competition, partially because of the internet. “Competition is up — way up. Back in 2006, we were battling for inches on a four-foot shelf. Now we’re battling for space on the internet shelf.”

Content marketing types have shifted. In 2006, “Buyers read stuff all day,” Halligan said, referring to blogs, product reviews and the like. Today, buyers mostly watch videos. At the time, Google and text formed a solid marriage, enabling online searchers to get their questions answered. “Google and text — that was like pigs in a blanket. In 2016, there’s another delicious combination: That’s video and social. That’s like scallops and bacon — just a delicious combination,” he noted. Halligan said that video and social enables marketers to share messages in new, viral ways but also that users are less singularly focused.

“Buyers used to focus on one piece of content at a time; now they are looking at your content, then your competitor’s content, then posting on Twitter and Instagram, then having breakfast. Welcome to the buying generation,” Halligan said.

Companies now need effective marketing strategies on social media platforms. Halligan noted that social media platforms are essential to a healthy marketing strategy. “If you’re not marketing on Facebook, Twitter or Instagram, you might as well be marketing inside a trashcan. If you’re not marketing inside the [Mark] Zuckerberg universe, you might as well be marketing inside a trashcan.”

Search has changed. Since 2006, Google has become more than just a search engine. In 2006, Google helped searchers find answers to a question. Today, Google just gives them the answer itself. But just as much as organic search has become an important element in the marketing playbook, Halligan noted that paid search has also become critical since 2006. “In 2006, ads took up about 50% of the screen above the fold,” Halligan said. “Today, it takes up 100% of the screen above the fold. Increasingly, buyers are clicking on AdWords. AdWords has gone up in my mind.” As HubSpot CTO and co-founder Dharmesh Shah noted, “You’re going to have search everywhere,” from Amazon to the Echo, to Siri to your car.

The buying process becomes more multichannel, more personalized, more self-service. Because online research has become so critical, content has become more important to the sales process than the sales rep, in some cases. “In 2006, the website augmented the sales rep. In 2016, the sales rep augments your website,” Halligan said. Companies like Airbnb and Uber have changed the nature of how prospects shop and buy with their “killer end-to-end processes” for consumers, Halligan noted.

Halligan gave marketers some advice in the new era:

Video is the new black. Stop looking for a blogger. Start looking for a videographer.

Accelerate your market. Divide your paid and content marketing. Repurpose your content on Twitter and Instagram. That is the power of content marketing.

Automate. Users are expecting you to automate their processes and offer self-service.

How a new sales cycle has changed sales

Why cold calling is dead. Halligan noted that many of the brute-force methods of traditional sales have been challenged by the web, self-service and multichannel customer service. “Your prospects hate cold calling,” Halligan said. “I’m going to go on record in front of 19,000 of my closest friends and say, ‘The cold call is dead.'” Halligan noted that in his research on successful sales, not a single purchase started with a cold call.

Why email messages are alive. Halligan said he thought self-service and online content might also have unseated traditional email in the sales cycle. But, he added, “I thought email was going to be dead, but it wasn’t. It’s alive and well. I looked at purchases and traced them to the original content that triggered the sale. In many cases, it started with an email, but the message had to be good — they didn’t just put the right name on their message but spent time creating a thoughtful email.”

Why product trials make a difference. Back in 2006, customers expected to get value after they purchased a product. Today, they expect to get value before. Dropbox provides freeware, and consumers can try the product for 100 days before they spend any money. In an era of supply outstrips demand, you have to change your tactics. Halligan referenced the David Mamet film Glengarry Glen Ross, which depicted the cutthroat nature of sales. At that time, a sales manager intoned that “coffee is for closers.” But today, Halligan said, “Coffee isn’t for closers; it’s for helpers.”

Halligan had some advice for sales reps as well:

Email. Less is more.

Cold calls. None is more.

Trials. A taste is more. “Let them eat cake by the ocean,” he quipped.

The buying process and the customer channel. While sales reps still have power, they exert it later in the process. Prospects spend half of their time researching content, then half the time talking to reps. Further, customers have become key sources for buying decisions. According to Halligan, two of top three most trusted sources for buying decision are customer reviews and comments, not marketers or salespeople.

Halligan concluded that in a world where supply is up and demand is flat, instead of squeezing value from customers you have to add value to their experience. “You can’t outgrow the phase where you’re adding value to your customers,” Halligan said.

The Channel

Where do we start when discussing the evolution of the digital channel? The evolution has dominated consumer options, giving rise to social networking, SMS, big data, CRM tools, and apps, which are just a few of the digital solutions available now.

In 2003 we weren’t thinking about social media, but we certainly are now, and we’ve also got a welter of new tools to work with new channels. Marketing automation is a reality today where marketers can manage many of those tools in one dashboard, and leverage all their respective digital assets to proactively reach out and provide and insights and options for their prospects and clients alike. The next step, the ability to manage leads and customer on an account basis, is already here.

The groundwork has been laid to establish a fully functional digital marketing product that places the management of the outreach directly into the marketer’s digital toolkit. To survive in this new normal marketers, both large and small, will need to understand, embrace and implement into their programs all the necessary initiatives that exist, so they can reach their intended recipients at every stage of the lifecycle, from dawning awareness to the advocacy of a satisfied customer.

The good news: You have options and should adopt multiple marketing outreach strategies to connect with your customer when and wherever he or she may be. Transactions that begin on a laptop may be finalized on a mobile device; make sure your communications are consistent across all channels.

The bad news: The pace of change is daunting and could create confusion for the user.

Paleoanthropologist Daniel Lieberman chewed raw goat meat for the sake of science, so he knows from experience that it’s a challenge.

“It’s a little salty, and it’s very tough,” the Harvard University professor said. “You put it in your mouth and you chew and you chew and you chew and you chew, and nothing happens.”

As Lieberman discovered first hand, modern human teeth are not suited to breaking chunks of raw meat into pieces that are small enough to swallow.

Effective raw-meat eaters like wolves and lions have teeth that are designed for slicing through elastic muscle, almost like a pair of scissors. Humans, on the other hand, have teeth that act like a mortar and pestle. Our pearly whites are designed for crushing, not slicing. When we chew on raw meat, the meat does not break apart.

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“It stays like a wad in your mouth,” Lieberman said. “It’s almost like a piece of chewing gum.”

Still, the fossil record suggests that ancient human ancestors with teeth very similar to our own were regularly consuming meat 2.5 million years ago. That meat was presumably raw because they were eating it roughly 2 million years before cooking food was a common occurrence.

Yet oddly, these meat-eating hominims had smaller teeth compared to their mostly vegetarian predecessors, as well as reduced chewing muscles and a weakened bite force, anthropologists say.

“With the advent of our genus, we start to see this suite of changes that continue on throughout time,” said Katherine Zink, a human evolutionary biology researcher at Harvard. “In general, we see decline in tooth size and jaw size.”

It is a seemingly strange evolutionary choice. Why would our ancient ancestors have a reduced ability to chew just after their diet became more gamy? Keep in mind that around the same time, their brains got larger, and their foraging ranges increased, causing their energy needs to grow.

A study published Wednesday attempts to address this paradox.

Writing in the journal Nature, Zink and Lieberman propose that the rise of meat-eating in hominims was possible only after our ancestors began using stone tools to help them process their food.

After running a series of tests in the lab, the authors report that hominims eating a diet composed of one-third meat and two-thirds root vegetables like beets and carrots, would see a 17% reduction in the number of chews required to ingest their food if the meat was first sliced with a sharp stone tool, and the root vegetables were pounded with a rock.

That equates to 2.5 million fewer chews per year, Zink said.

To come to this conclusion, Zink recruited more than a dozen chewers — most of them colleagues in the Human Evolutionary Biology department at Harvard. (Lieberman offered himself up as an early guinea pig, although his personal chewing results were not included in the paper).

Eight electrodes were attached to each volunteer’s face to measure the activity of four distinct chewing muscles — one on either side of the jaw bone, and one at each temple. An electrode also was attached to each participant’s hand to filter out background activity.

In addition, the chewers were outfitted with a dime-size force transducer that was placed between the first left molars. This allowed the researchers to measure chewing force.

The subjects then were given different samples of meat and raw vegetables to chew. Some of the samples were completely unprocessed, while others were sliced or pounded with a stone tool before being handed over. Still others were roasted.

Raw goat meat was used in the tests because it was the closest approximation of wild game that Zink could find. She said that it was frozen and then tested for pathogens before being thawed and fed to participants.

Volunteers were asked to chew each sample until they would typically swallow their food — usually about one minute or 20 to 40 chews. At that point, they spit their food out so that the particle sizes could be measured.

Researchers found that humans are simply not able to consume meat without some sort of processing, but that the rudimentary slicing of meat allowed it to be broken down into small enough pieces to be swallowed.

They also found that cooked meat requires more force to chew than raw meat, but because the fibers are stiffer, it can be broken down between the teeth.

Based on this evidence, the researchers argue that simple mechanical processing would have been required for our ancestors to make meat a regular part of their diets. They also say that the ability to process this meat allowed for the selection of smaller jaws and teeth that is evident in the fossil record.

“We didn’t just start eating meat,” Lieberman said. “We had to invent some technology in order to be able to do it.”

Zink and Lieberman further reason that once the mechanical work of breaking down food could be started outside the oral cavity, it would have left our ancestors free to use their mouths for other things besides chewing — like talking.

“If you are using less force and using fewer chews, you are, of course spending less time eating,” Zink said. “And if you no longer need to maintain the big jaws and big teeth, it allows natural selection to choose for other performance benefits that improve fitness and survival.”

David Strait, a physical anthropologist at Washington University in St. Louis who was not involved with the study said Zink and Lieberman are not the first to address how slicing or pounding food may have affected human evolution, but they are the first to use experiments to examine the issue.

“This means that previously we were speculating, but now we have actual data,” he said. ” And that is a good thing.”